CN103557870B - Dynamic trajectory navigation method and cloud platform - Google Patents

Dynamic trajectory navigation method and cloud platform Download PDF

Info

Publication number
CN103557870B
CN103557870B CN201310466623.3A CN201310466623A CN103557870B CN 103557870 B CN103557870 B CN 103557870B CN 201310466623 A CN201310466623 A CN 201310466623A CN 103557870 B CN103557870 B CN 103557870B
Authority
CN
China
Prior art keywords
section
cloud platform
track
mobile terminal
path planning
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201310466623.3A
Other languages
Chinese (zh)
Other versions
CN103557870A (en
Inventor
董路
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN201310466623.3A priority Critical patent/CN103557870B/en
Publication of CN103557870A publication Critical patent/CN103557870A/en
Priority to PCT/CN2014/087686 priority patent/WO2015051718A1/en
Application granted granted Critical
Publication of CN103557870B publication Critical patent/CN103557870B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Navigation (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention is applicable to the field of navigation and provides a dynamic navigation route planning method and a cloud platform. The method comprises the following steps that: the cloud platform wirelessly receives multiple trajectory information uploaded by a plurality of mobile terminals or existing real-time route planning schemes of the plurality of terminals in real time and updates and improves a dynamic road section database in the cloud platform by using the multiple trajectory information or the existing real-time route planning schemes of the plurality of terminals; and when the cloud platform receives a route planning request with specific requirements brought forward by one mobile terminal, the cloud platform calculates a corresponding route plan according to data of the updated and improved dynamic road section database in the cloud platform and sends the route plan to the mobile terminal in a wireless mode. The method and the cloud platform provided by embodiments in the invention realize large scale utilization of the mobile terminals for acquisition of trajectory information, application of the trajectory information as dynamic traffic information, precise navigation, accurate prediction, reasonable dodging from a jammed road and accurate avoidance of driving to roads closed to passage.

Description

A kind of dynamic trajectory air navigation aid and cloud platform
Technical field
The invention belongs to navigation field, relate in particular to a kind of dynamic trajectory air navigation aid and cloud platform.
Background technology
Be accompanied by the day by day deep of the development of mobile Internet, cloud computing, ITS intelligent transportation system, car working application technology and wisdom urban construction, and China second generation Beidou satellite navigation system BD2's is full-fledged, it is more and more important also more and more urgent that the further investigation of dynamic navigation technology seems.
Definition and the static traffic restricted information of section, node, shape value point.In actual conditions, for fear of the topological relation between worry about road, the general road junction that extracts in road network figure is as the object of analyzing, and to define this intersection be one of node, and node also can comprise the place that roadhead or road attribute change; Road is cut apart with node, and the one section of road defining between two nearest nodes is section simultaneously.Like this, whole road network figure will be comprised of node and section, the node that crossroad stomion is network, and the arc that section is network, interconnective some the sections that title is identical have formed a road.Section can be described with broken line, is called road shape value point on the summit of broken line turning point.Shape value point is present on section, and the part between 2 adjacent shape value points is called the sub-section in this section.Static traffic restricted information refers in an actual traffic network, the fixing traffic restriction that can not change in the long period: one-way road, and no turn, no turns.Process this information, first need to set up the model of road topology relation and obtain the method for expressing to static traffic restricted information, make these information can be fused in traffic network model and can be identified easily and store by system.
The collection of Real-time Traffic Information.In the past, transport information obtain the traffic flow checkout equipment mostly depending on road, as toroidal inductor, radar, video photo, license plate identification, infrared sensor and unsteady vehicle (FC) etc.Nearly one, two year just starts to gather traffic information with mobile terminal, such as now, is mainly that the driving trace at the taxi with a large amount of enriches Real-time Traffic Information, particularly as the main information source of real-time road.
The prediction of road traffic condition.Because traffic information changes, if the selected route of the transport information before traveler sets out by him, perhaps, when he arrives certain crossing, road has become crowded to capacity smoothly.So the traffic of real-time estimate road in following certain period is most important to accurate navigation.At present, not remarkable to the research effect of this aspect.
In realizing the technical scheme of prior art, find that there are the following problems:
Due to the restriction of wireless communication technology in the past, the shortage of the scarcity of mobile Internet terminal and cloud platform, cannot realize technically on a large scale and come acquisition trajectories information as dynamic transport information with mobile terminal, cause going back up to now the ripe effectively dynamic navigation method of neither one.And approach the most the external INRIX that has the U.S. of this technology, domestic have Gao De, four figure reform, the so-called optimal path that they can calculate according to real-time road condition information, but also just rely on road data on original map and the congestion information qualitatively on red greenish-yellow trunk roads, carry out computing, the path planning providing is often still very unreasonable; And as an importance---the prediction of future trajectory traffic of dynamic navigation technology, up to now, also more satisfactory model and the method for neither one.
Summary of the invention
The object of the embodiment of the present invention is to provide a kind of dynamic trajectory air navigation aid of cloud platform central controlled, is intended to solve in the quantitative calculating that prior art cannot directly apply to trace information path planning, causes that path planning is unreasonable, the insensitive problem of reaction road condition change; A kind of method of brand-new predicted congestion road conditions is provided simultaneously, and can calculates according to predicting the outcome the shortest path planning scheme of a kind of running time; And this Forecasting Methodology is that the existing real-time route programme of the terminal of using of uploading according to relevant mobile terminal draws, thereby when relevant mobile terminal quantity is abundant, this Forecasting Methodology is reliable.
On the one hand, provide a kind of dynamic navigation path planning method, described method comprises:
Cloud platform real-time radio receives a plurality of trace informations or the existing real-time route programme of a plurality of terminal that a plurality of mobile terminals are uploaded, then utilize described a plurality of trace information or a plurality of terminal to have real-time route programme, upgrade and improve the dynamic section database of cloud platform inside;
When a certain path planning request that has a particular requirement that cloud platform receives that mobile terminal proposes, cloud platform is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculate and a certain corresponding path planning of path planning request that has particular requirement, then corresponding path planning is sent to mobile terminal with wireless mode;
Described trace information comprises: the quantity of track and the acquisition time of track, the longitude and latitude of track each point and acquisition time, elevation and acquisition time, two dimension or three-dimensional velocity and acquisition time, two dimension or three-dimensional motion direction and acquisition time, video or photograph image and acquisition time, the code of mobile terminal under track; The quantity of described track, refer in added up time range and spatial dimension, continuous two dimension or three-dimensional locus coordinate points that each mobile terminal is uploaded are connected to form a track by the time sequencing by after arriving first, then cumulative track number described in these, drawn quantity;
The existing real-time route programme of described terminal refers to that described mobile terminal is Already in inside, that using, this uploads location while starting to the scheme of travelling of destination from described mobile terminal, and it can be told described in cloud platform, and mobile terminal starts wherefrom, which way to go, will be where; Main effect is for the congestion of predict future road, and it is constantly to change along with the continuous movement of mobile terminal; In fact, it is also similar to a track----mono-track that may form future; It does not refer to cloud platform path planning that make to mobile terminal and that will send to mobile terminal.
If a vehicle that is numbered No. 1 drives towards another node W from the node V of a section VW, if t1v is the moment of No. 1 vehicle arrival node V, T1vw(t1v) be that No. 1 vehicle arrives the spent time of node W, consuming time, consuming time in certain time zone T of n vehicle: T1vw(t1v), T2vw(t2v), ... weighted mean Tnvw(tnv), formed average consuming time, this average definition of T pnvw consuming time, be also referred to as section vw at T time zone the motional impedance from V to W.If this time zone T is co-occurrence, having the corresponding time of passing by of trace information, is instant motional impedance; If this time zone T is following time zone of a certain appointment, the motional impedance calculating by this future time region T and the existing real-time route programme of terminal, cloud platform historical data so, is called prediction motional impedance.
Inner at a cloud platform, the trace information of uploading in real time and the existing real-time route programme of terminal with a plurality of mobile terminals, generate and upgrade new section, generation and renewal simulation traffic restricted information, generation and the instant motional impedance of renewal, generation and renewal prediction motional impedance, the database in the dynamic relevant section of of forming is like this called dynamic section database.
Described renewal and improve the dynamic section database of cloud platform inside, refer to according to the trace information that comprises the quantity of track and the acquisition time of track, generate and upgrade the simulation traffic restricted information in instant motional impedance, generation and all sections of renewal in section data, generation and all sections of renewal on unknown road, in addition, according to the existing real-time route programme of described a plurality of terminals and track historical data, generate and upgrade the prediction motional impedance in all sections;
Described all sections refer to and comprise newly-generated section and original section; The acquisition time of described track, refers to one and time set corresponding to each point that the acquisition time of the longitude and latitude that forms track each point forms; The acquisition time of the longitude and latitude of described track each point, refers to mobile terminal residing moment when getting the latitude and longitude coordinates of described each point.
Second aspect, provides a kind of cloud platform, and described cloud platform comprises a plurality of smart machines, and described smart machine comprises: processor, storer, communication interface and bus;
Described communication interface real-time radio receives a plurality of trace informations or the existing real-time route programme of a plurality of terminal that a plurality of mobile terminals are uploaded, then processor utilizes described a plurality of trace information or the existing real-time route programme of a plurality of terminal, upgrades and improve the dynamic section database of cloud platform inside; When a certain path planning request that has a particular requirement that communication interface receives that mobile terminal proposes, processor is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculate and a certain corresponding path planning of path planning request that has particular requirement, then corresponding path planning is sent to mobile terminal with wireless mode;
Described trace information comprises: the quantity of track and the acquisition time of track, the longitude and latitude of track each point and acquisition time, elevation and acquisition time, two dimension or three-dimensional velocity and acquisition time, two dimension or three-dimensional motion direction and acquisition time, video or photograph image and acquisition time, the code of mobile terminal under track; The quantity of described track, refer in added up time range and spatial dimension, continuous two dimension or three-dimensional locus coordinate points that each mobile terminal is uploaded are connected to form a track by the time sequencing by after arriving first, then cumulative track number described in these, drawn quantity;
That the existing real-time route programme of described terminal refers to is that mobile terminal is being used, from this, upload the ground at the place while starting to a path planning scheme of destination;
Described renewal and improve the dynamic section database of cloud platform inside, refer to according to the trace information that comprises the quantity of track and the acquisition time of track, generate and upgrade the instant motional impedance in the section data on unknown road, all sections and the simulation traffic restricted information in all sections, in addition, according to the existing real-time route programme of described a plurality of terminals and track historical data, generate and upgrade the prediction motional impedance in all sections;
Described all sections refer to and comprise newly-generated section and original section; The acquisition time of described track, refers to one and time set corresponding to each point that the acquisition time of the longitude and latitude that forms track each point forms; The acquisition time of the longitude and latitude of described track each point, refers to mobile terminal residing moment when getting the latitude and longitude coordinates of described each point.
In embodiments of the present invention, technical scheme provided by the invention has advantages of that realization carrys out acquisition trajectories information as dynamic transport information and carries out precisely rationally navigating with mobile terminal on a large scale.
Brief Description Of Drawings
Fig. 1 is the process flow diagram of a kind of dynamic navigation path planning method of providing of the specific embodiment of the invention;
Fig. 2 is the structural representation of the cloud platform that provides of the specific embodiment of the invention.
Implement mode of the present invention
In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
The present invention the most significantly one of creativeness is that the solid-state section database in navigational system is changed into the dynamic section database changing with trace information.
The present invention the most significantly one of creativeness is that the existing real-time route programme of the terminal of a plurality of mobile terminals is uploaded to cloud platform center in real time, and calculate prediction motional impedance according to the historical data in the existing real-time route programme of described terminal and cloud platform, as predict future road congestion conditions and calculating path planning.
The present invention can be described as a cloud computing, large data, mobile Internet, car networking, Big Dipper navigation product of the time.Because the quantity of a plurality of trace informations uploaded described in this technology refers to the order of magnitude of data so-called magnanimity, large, that is to say that described a plurality of trace informations refer to magnanimity be ten hundreds of or the hundred million above orders of magnitude, continuously dense trace information flows, only have in this case, by track quantity, carry out the effect that correlation computations just has.
The present invention the most significantly one of creativeness is that the main body of path planning is transferred to Yi Ge control center by original mobile terminal---cloud plateform system is inner, and the solid-state section database that is generally in this cloud plateform system is changed into the dynamic section database changing with trace information; This technology has been used cloud computing technology simultaneously; adopted the trace information of magnanimity; and calculating so-called large data according to statistical principle, the quantity of use track and track acquisition time, as Important Parameters, carry out dynamic section database real-time, that change dynamically cloud platform inside.
The embodiment of the present invention is to realize like this, comprising under GPS or BD2 positioning system, a cloud computing platform real-time radio receives client in all systems and is loaded in the mobile terminal on vehicle---there is the locating device (as taxi locating and monitoring equipment) of communication function or the trace information that guider (as smart mobile phone) sends, then process and computing, dynamically upgrade the section database of cloud platform inside, generate instant motional impedance weights and prediction motional impedance weights, or generate new section, simulation generates new traffic restricted information, when receiving the path planning request of mobile terminal proposition, the dynamic section database data that cloud platform has upgraded according to these calculates a path planning, send to again mobile terminal.The main technical principle of specific implementation is: by the trace information receiving, give up abnormity point, and carry out Kalman filtering processing, remove noise, then the original section data in GIS are carried out to projection, as success changes the instant motional impedance weights in this section with the time data comprising in trace information; As unsuccessful, generating in addition interim section stores in the database of section and generates voluntarily instant motional impedance weights.When client proposes quickest routing planning, first according to conventional shortest path first (as A* algorithm), obtain n bar shortest path, in n bar shortest path, can comprise newly-generated section, and then in this n paths planning, according to the stack of the instant motional impedance weights in comprised section, select overall the shortest path planning consuming time, be quickest routing planning.Meanwhile, the real-time route planning that also can upload according to a plurality of mobile terminals, calculates the prediction motional impedance in following some time section, and is applied in the calculating of some path planning.
Described cloud platform is cloud computing platform, refer to a kind of have superpower storage and computing power, based on internet, its storage and computational resource magnanimity, as required Dynamical Deployment, dynamic optimization, dynamically regain, with a series of computation group of planes and the data platform of virtual mode shared resource.Because the described a plurality of mobile terminals in this technology, what in fact refer to magnanimity is mobile terminals ten hundreds of or the hundred million above orders of magnitude, the trace information that here mobile terminal is uploaded is defined as a trace information, and a plurality of trace informations, what refer to magnanimity is ten hundreds of or the hundred million above orders of magnitude, dense trace information stream continuously, only have this cloud platform with superpower computing power of use, just likely complete this numerous and diverse calculation task.
Compared with prior art, beneficial effect is the embodiment of the present invention: the data that the present invention adopts are trace informations comprehensive, continuous, numerous and diverse, magnanimity, thus because of sample size large with a high credibility; It collects storage and calculating and path planning is to carry out in the inside of a cloud platform, and calculated amount is large, speed is fast; And have advantages of dynamic, can utilize the new road not having on map implement navigation, can utilize trace information upgrade calculated population path planning traffic restricted information, can be quantitative dynamically consuming time, can real time reaction road condition change; The existing real-time route programme of terminal that also can use according to numerous relevant a plurality of mobile terminals in addition, the congestion in certain section during predict future.
It should be noted that, the above-mentioned method that comprises the Regeneration dynamics section database that generates new section, should take do not violate concerned countries about the rules law of mapping aspect be prerequisite.
The specific embodiment of the invention provides a kind of dynamic navigation path planning method, and the method as shown in Figure 1, comprising:
101, cloud platform real-time radio receives a plurality of trace informations or the existing real-time route programme of a plurality of terminal that a plurality of mobile terminals are uploaded, then utilize described a plurality of trace information or a plurality of terminal to have real-time route programme, upgrade and improve the dynamic section database of cloud platform inside;
102, when a certain path planning request that has a particular requirement that cloud platform receives that mobile terminal proposes, cloud platform is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculate and a certain corresponding path planning of path planning request that has particular requirement, then corresponding path planning is sent to mobile terminal with wireless mode;
The existing real-time route programme of above-mentioned terminal refer to that mobile terminal is inner existing and using, from described mobile terminal, this uploads location while starting to a path planning scheme of destination;
Described trace information comprises: the quantity of track and the acquisition time of track, the longitude and latitude of track each point and acquisition time, elevation and acquisition time, two dimension or three-dimensional velocity and acquisition time, two dimension or three-dimensional motion direction and acquisition time, video or photograph image and acquisition time, the code of mobile terminal under track;
Described renewal and improve the dynamic section database of cloud platform inside, refer to according to the trace information that comprises the quantity of track and the acquisition time of track, generate and upgrade the instant motional impedance in the section data on unknown road, all sections and the simulation traffic restricted information in all sections, in addition, according to the existing real-time route programme of described a plurality of terminals and track historical data, generate and upgrade the prediction motional impedance in all sections;
Described all sections refer to and comprise newly-generated section and original section; The acquisition time of described track, refers to one and time set corresponding to each point that the acquisition time of the longitude and latitude that forms track each point forms; The acquisition time of the longitude and latitude of described track each point, refers to mobile terminal residing moment when getting the latitude and longitude coordinates of described each point.
The quantity of described track, refer in added up time range and spatial dimension, continuous two dimension or three-dimensional locus coordinate points that each mobile terminal is uploaded are connected to form a track by the time sequencing by after arriving first, then cumulative track number described in these, drawn quantity; That the existing real-time route programme of described terminal refers to is that mobile terminal is being used, from this, upload the ground at the place while starting to a path planning scheme of destination.
Optionally, above-mentioned generation and the method for upgrading the section data on unknown road comprise: when a plurality of mobile terminals travel on unknown road, when its trace information of uploading can not match in the dynamic section database of cloud platform in the data of original section, cloud platform is by the trace information on original section in the dynamic section database that can not match cloud platform described in these, give up abnormity point, remove noise, and arrange and be merged into a simulated roadway according to a certain method, and keep in the database of dynamic section, calculate the track quantity in simulated roadway simultaneously; When in interval sometime, when being incorporated in track quantity on this simulated roadway and reaching a certain setting threshold, cloud platform is transformed into one or several new temporary or permanent newly-generated section data by this simulated roadway, store in the database of dynamic section, cloud platform is also constantly updated described newly-generated section data according to the new trace information of uploading in real time; It should be noted that described removal noise can adopt Kalman filtering algorithm to realize.
Dynamic section database in this cloud platform of above-mentioned renolation specifically can adopt any one or the combination in following manner:
The quantity of track that mode A, cloud platform are uploaded in real time according to a plurality of mobile terminals and the acquisition time of track, calculate on a certain section the on average consuming time of the track in region sometime, and average consuming timely as an instant motional impedance, be stored in a database using described, described a certain section is newly-generated section on section on original road or unknown road;
When the mode of employing A, the path planning request of a certain particular requirement proposing when mobile terminal is: during the path planning request of shortest time, described cloud platform is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculating a certainly has the corresponding path planning of path planning request of particular requirement specifically to comprise: the database data that has comprised these instant motional impedances for cloud platform, calculated population the shortest path planning consuming time.
Mode B, cloud platform store the acquisition time that is included in the track that numerous mobile terminals of travelling on original road and unknown road upload in the dynamic data base of cloud platform into, and the acquisition time of described track is associated with the acquisition time corresponding road section of described track; When mobile terminal is set a time zone; and file a request: when some are stored in track acquisition time in described dynamic data base while falling into described in this time zone; find out the corresponding track of these acquisition times; find out again the section at the track place of described correspondence; then with these sections, splice a path planning; cloud platform is used qualified section according to the request of mobile terminal, calculates path planning.
The quantity of the track on certain section that mode C, cloud platform are uploaded numerous terminals, stores in the database of cloud platform, and is associated with corresponding road section; When mobile terminal is set an amount threshold, and when proposing track quantity on some sections and falling into this amount threshold, find out these sections, while then splicing the request of a path planning with these sections, cloud platform is used qualified section according to the request of mobile terminal, the planning of splicing outbound path.
Mode B and mode C can also be combined with, within choosing certain a period of time, have the section of certain certain track quantity, carry out stitching path planning.One of meaning of doing is like this: can avoid because the reasons such as maintenance or accident cause sealing some forbidden sections, because in this case, the track of vehicle quantity of sealing in forbidden time zone at this in these sections obviously trends towards zero.And existing technology but can not be identified this common situation.
Optionally, said method also comprises between 101 and 102:
By check in unknown road and the original road track quantity on region, a certain appointment section sometime, simulation generate forbid allowing turning, turning traffic restricted information, allow to turn around, no turns traffic restricted information or one-way road traffic restricted information.
Optionally, simulating to generate allows turning or no turn traffic restricted information to comprise: whether two crossing sections of cloud platform check own the track of certain travel direction of continuous same mobile terminal formation together, and calculate in the time zone of a setting quantity of track described in this class, or the relative populations of comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information that can turn according to track travel direction at crossing node between these two sections, store in a special database, otherwise, when this result of calculation is less than a value of setting in advance, simulation generate between these two sections at crossing node according to the traffic restricted information of track travel direction no turn, store in a special database.
Optionally, above-mentioned simulation generates and allows to turn around or no turns that traffic restricted information comprises: cloud platform checks some sections whether to exist to take the forward of the continuous formation of same mobile terminal that certain shape value point is turning point and reverse track, and calculate in the time zone of a setting quantity of track described in this class, or, the relative populations of comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information that can turn around according to described track turnover direction at this turning point between this section, store in a special database, otherwise, when this result of calculation is less than a value of setting in advance, simulation generates the traffic restricted information that forbidding between this section turn around according to described track turnover direction at this turning point, store in a special database.
Above-mentioned simulation generates one-way road traffic restricted information and comprises: the track quantity that cloud platform checks the mobile terminal of certain direction of section of certain to form, and calculate in the time zone of a setting quantity of track described in this class, or, the relative populations of comparing with track rightabout or that other are relevant, when this result of calculation is less than a value of setting in advance, simulation generates this section direction traffic restricted information that no through traffic described in this, stores in a special database.
Optionally, above-mentioned cloud platform calculates corresponding path planning according to described renewal and the data of improving the dynamic section database of described cloud platform inside and comprises:
Cloud platform first adopts static conventional shortest path computing method to calculate the shortest path planning scheme of n bar overall distance, in n bar shortest path planning scheme, according to the instant motional impedance on section, place, select an overall the shortest paths planning consuming time again, described section comprises: the section on original road and unknown road.
The conventional shortest path computing method of above-mentioned static state, refer to a kind of being referred to as: A* heuristic search algorithm; This algorithm is for calculating the shortest path planning scheme of n bar overall distance according to the dynamic section database data of described renewal and perfect cloud platform inside; Described A* heuristic search algorithm, is limited to a kind of special case of 0 A* heuristic search algorithm: dijkstra algorithm under comprising.
Optionally, above-mentioned these trace informations that utilize upgrade and improve the section database in this cloud platform inside, refer to the new section data that simulation generates according to trace information are stored in a database of expressing in adjacency list mode together with original section data.
Optionally, above-mentioned cloud platform, according to these renewals and perfect section database data, calculates corresponding path planning and specifically comprises:
By the elevation in trace information and two dimension or three-dimensional motion directional information, with section, place, be associated and weighted mean after be stored in database together with same video, picture data, in order to distinguish approximate section; When cloud platform is with comprising overpass difference but surface level position is close or identical or that other highly identical but horizontal level approaches when path planning is carried out in approximate section described in some highly up and down, the latitude and longitude coordinates of the described approximate section of cloud platform check node, when the corresponding differences of longitude coordinate value of node in two sections and the absolute value of the difference of latitude coordinate values are less than the value of a setting simultaneously, automatically read the trace information that can comprise dispersed elevation, travel direction, video, photo travelling at described two mobile terminals above section; Can also calculate the joining relation in described two sections and adjacent section, front and back separately simultaneously, the row labels of going forward side by side and prompting, be stored in together in the database of dynamic section, cloud platform is according to being stored in described trace information and the joining relation in the database of dynamic section, and calculating path is planned; Then by the trace information that can comprise dispersed elevation, travel direction, video, photo of described mobile terminal and described joining relation together with mark and prompting, with the path planning scheme calculating together, send to mobile terminal; Described link for calculating relation, refer to that each mobile terminal being accumulated on certain section is in the quantity of keeping straight on or turning, crossing over the continuous path forming when node drives to adjacent section, when this quantity falls into the threshold value of a setting in the time zone of a setting, or when in the time zone of a setting, by the quantity of described continuous path, with relevant track quantity, compare, when its ratio falls into the threshold value of a setting, confirm as these two sections has joining relation in the direction of this track operation.
Optionally, the above-mentioned dynamic section database that utilizes described trace information and the existing real-time route programme of terminal to upgrade and improve cloud platform inside, refer to the existing real-time route programme of terminal that cloud platform is uploaded dynamically in real time according to a plurality of mobile terminals, and the instant motional impedance of the nearlyer a period of time in involved section, calculate a pre-quantitation of the mobile terminal on following a certain section of certain fixed time, then according to this pre-quantitation, found out the weighted mean value of the instant motional impedance in upper certain a period of time in this corresponding section of the quantity therewith of storing in cloud platform, prediction motional impedance as this section, store into together in a database of cloud platform with the corresponding time, when a mobile terminal proposes a certain specific path planning, cloud platform is according to predicting motional impedance described in this, the predict future fixed time, certain specifies the traffic congestion situation in section, and calculate a path planning scheme by mobile terminal requirement, radio to mobile terminal.
Optionally, described cloud platform, according to these renewals and perfect section database data, calculates corresponding path planning and specifically comprises:
The method of the mode of its renolation and calculating path planning can as required, be used in combination the technical scheme of said method confession.
Mobile terminal, after receiving the path planning scheme of cloud platform wireless transmission, has three kinds of situations:
Section database data in a, cloud platform and mobile terminal identical, the path planning scheme that mobile terminal is made according to cloud platform, directly splices by local corresponding road section;
B, map in cloud platform and the map homologous ray different editions in mobile terminal, although or the data of homologous ray with version but in the database of section are different, at this moment the main problem producing is that the section that has on cloud platform but mobile terminal map do not have, for addressing this problem, should be in advance by special database design and the foundation of topological relation, make as far as possible the section database of two homologous ray different editions there is highly compatible, like this, cloud platform just can be first by detecting, the continuous section data message arranged in sequence of owning together is out sent to terminal, then mobile terminal is carried out according to the method in above-mentioned a., for the section data division that has in cloud platform but do not have in mobile terminal, cloud platform sends to mobile terminal by the longitude and latitude data of the location point in this part section data, mobile terminal is found out corresponding location point according to these longitude and latitude data again, and line and showing in display screen, in voice message, point out: " unknown road, please by trace information careful driving " simultaneously.
C, for the electronic chart of different system, will be according to the world or relevant national standard, all convert road section information to trace information, be about to whole path planning schemes and send to mobile terminal with the form of trajectory location points longitude and latitude data, mobile terminal draws accordingly line and supplies driver's reference on screen, follow transmission voice message: " track navigation, please by track careful driving simultaneously." like this, will be conducive to serve to greatest extent various client.
It should be noted that, the trace information of above-mentioned explanation, both can be to comprise adopting GPS/DR, the satellite positioning tech of BD2 (second generation triones navigation system)/DR mobile terminal locating module, the trace information that mobile communication base station location technology gathers, also can be by adopting RFID recognition technology, the electronic recognition technology of infrared or laser scanner technique and so on, identification is loaded in the trace information that the electronic tag on vehicle obtains, can also comprise the trace information obtaining with video and image information mode, the acquisition mode of above-mentioned trace information should not be subject to the restriction of acquisition method.
For protection user's privacy, the collection of the existing real-time route programme of described trace information and terminal can adopt anonymous way to obtain.Uploading or the reception of path planning of trace information between mobile terminal and cloud platform, its communication also can be for multiple, the short message communication, WiFi, GPRS, 2G, 3G or the 4G technology that comprise satellite communication, Beidou satellite navigation system, which kind of communication is the specific embodiment of the invention be not limited to.
It should be noted that, above-mentioned trace information can comprise: code, video and the image different kinds of parameters of mobile terminal under the quantity of the longitude of track each point, latitude, elevation, two dimension or three-dimensional velocity, two dimension or three-dimensional motion direction, track, track, and the acquisition time of described different kinds of parameters; Described renewal and improve the dynamic section database of cloud platform inside, refer to according to the different kinds of parameters comprising in the trace information in the quantity of track and the acquisition time region of track, generate and upgrade section data on unknown road, the instant motional impedance on all sections, the simulation traffic restricted information on all sections.One of its concrete grammar is: cloud platform receives after trace information, first it is carried out to filtering processing, remove abnormal or the excessive clutter of deviation, then according to certain method, the position data in trace information is matched with the original section data in GIS database, as success falls into this section data, the data change that is about to the point that track is corresponding with node path section is the data of section corresponding point, and gives this section instant motional impedance weights according to the acquisition time of track; As unsuccessful, store in another one database, and in this database, the track contiguous to position arranges merging, generate one or more simulated roadway, when in a fixed time region, when the track quantity on described simulated roadway reaches certain value, according to certain method, cut apart and simulate and generate new section.
In addition, also can generate and upgrade section and predict motional impedance according to the existing real-time route programme of a plurality of terminals.That the existing real-time route programme of described terminal refers to is that mobile terminal is being used, from this, upload the place at the place while starting to a path planning scheme of destination; Described instant motional impedance refers to that the weighted mean of calculating certain section time zone is consuming time according to the trace information of the described a plurality of mobile terminals that received, and obtains a result and is the instant motional impedance in described certain time zone section; Described prediction motional impedance refers to the existing real-time route programme of a plurality of terminals of uploading according to a plurality of mobile terminals, in conjunction with the historical data in cloud platform, calculate the consuming time of following certain time zone section, obtain a result and be the prediction motional impedance in described time zone in future section; Described all sections refer to and comprise newly-generated section and original section.
It should be noted that; track acquisition time described in the application; refer to the time set that the acquisition time of each location point that forms track forms; the acquisition time of described location point; refer to mobile terminal residing moment when collecting described location point longitude and latitude data; because the moment at mobile terminal place may have an error with the moment that collects data, so this acquisition time generally can lag behind the time of this location point of the actual place of mobile terminal a little.But in this technology, generally ignored this time difference.
It should be noted that, traffic restricted information described in this technology, refers to and comprises: no left turn, No right turn, no turns, forbid the traffic prohibitory sign category information of keeping straight on and turn left, bend to right, allow to turn around, one way traffic only collimates capable traffic direction sign category information.
Described cloud platform is according to prediction motional impedance, and the predict future fixed time, certain specifies the traffic congestion situation in section, and calculates a path planning scheme by mobile terminal requirement, is wirelessly sent to mobile terminal; Its meaning is also: can be used on the one hand the flow distribution of prediction and overall planning vehicle, on the other hand, when cloud platform and mobile terminal are enough fast to the computing velocity of the collection transmission speed of trace information, path planning scheme and wireless transmission speed, and be aided with the direct interchange of the described trace information between associated vehicle, can also, by automatic alarm, the mode of automatically evading, be used for preventing the collision between vehicle.
Need explanation be, described link for calculating relation, refer to the resulting quantity that each mobile terminal on cumulative certain section is crossed over the continuous path forming when node drives to adjacent section in craspedodrome or turning process, the relative value of comparing with other relevant track quantity when value or the described quantity of quantity described in this, while being greater than the value of a setting in the time zone of a setting, confirming as these two sections and take the node crossed over as being connected point, having joining relation in the direction of this track operation; The relative value of comparing with other relevant track quantity when value or the described quantity of quantity described in this, while being less than the value of a setting in the time zone of a setting, confirming as these two sections and take the node crossed over and as being connected, investigate point, in the direction of this track operation, there is no joining relation; And described there is no a joining relation here, comprise on physical condition as the restriction in the road of the upper and lower staggered floor of viaduct, guardrail, gully; Also comprise the upper as the restriction that mustn't keep straight on, mustn't turn of traffic rules.
In sum, the enforcement of this technology, will play certain impetus to the construction in the development of ITS intelligent transportation system, car working application technology and China's wisdom city.
The specific embodiment of the invention also provides a kind of cloud platform, this cloud platform comprises: many smart machines, this smart machine specifically can: computing machine or server, the hardware structure diagram of described smart machine as shown in Figure 2, comprising: processor 201, storer 202, communication interface 203 and bus 204.
Processor 201, storer 202, communication interface 203 interconnect by bus 204; Bus 204 can be Industry Standard Architecture system (Industry Standard Architecture, ISA) bus or peripheral component interconnect (English: Peripheral Component Interconnect, be called for short: PCI) bus etc.
Above-mentioned processor 201 can be general processor, comprise central processing unit (English: central processing unit, abbreviation CPU), network processing unit (English: network processor, be called for short NP), can certainly be digital signal processor (English: Digital Signal Processing, abbreviation: DSP) etc.
Storer 202, for depositing program and dynamic section database.Particularly, program can comprise program code, and described program code comprises computer-managed instruction, and this program is used to indicate processor 201 and sends computer-managed instruction.Storer 202 may comprise high speed random access memory (English: random-access memory, abbreviation: RAM) storer, also may also comprise nonvolatile memory (non-volatile memory), for example at least one magnetic disk memory.
Communication interface 203, for receiving or send data.Above-mentioned data are specifically as follows: the data such as message, trace information or path planning information, and particularly, this communication interface 203 can be communication port, this communication port includes but not limited to wireless communication port or wire communication port.
Communication interface 203 real-time radios receive a plurality of trace informations or the existing real-time route programme of a plurality of terminal that a plurality of mobile terminals are uploaded, then processor 201 utilizes described a plurality of trace information or the existing real-time route programme of a plurality of terminal, upgrades and improve the dynamic section database of cloud platform inside; When a certain path planning request that has a particular requirement that communication interface 203 receives that mobile terminal proposes, processor 201 is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculate and a certain corresponding path planning of path planning request that has particular requirement, then corresponding path planning is sent to mobile terminal with wireless mode;
The existing real-time route programme of above-mentioned terminal refer to that mobile terminal is inner existing and using, from described mobile terminal, this uploads location while starting to a path planning scheme of destination;
Described trace information comprises: the quantity of track and the acquisition time of track, the longitude and latitude of track each point and acquisition time, elevation and acquisition time, two dimension or three-dimensional velocity and acquisition time, two dimension or three-dimensional motion direction and acquisition time, video or photograph image and acquisition time, the code of mobile terminal under track;
Described renewal and improve the dynamic section database of cloud platform inside, refer to according to the trace information that comprises the quantity of track and the acquisition time of track, generate and upgrade the instant motional impedance in the section data on unknown road, all sections and the simulation traffic restricted information in all sections, in addition, according to the existing real-time route programme of described a plurality of terminals and track historical data, generate and upgrade the prediction motional impedance in all sections;
Described all sections refer to and comprise newly-generated section and original section; The acquisition time of described track, refers to one and time set corresponding to each point that the acquisition time of the longitude and latitude that forms track each point forms; The acquisition time of the longitude and latitude of described track each point, refers to mobile terminal residing moment when getting the latitude and longitude coordinates of described each point.
Optionally, processor 201 specifically for, when trace information that a plurality of mobile terminals are uploaded can not match in the dynamic section database of cloud platform in the data of original section, the described trace information that processor 201 can not mate these is removed noise, arrange and be merged into one or more simulated roadway according to a certain method, and keep in the database of dynamic section the track quantity simultaneously adding up in described simulated roadway; When setting at certain in a time interval, when the track quantity on certain described simulated roadway is added to a certain setting threshold, described processor is transformed into one or several new temporary or permanent newly-generated section data by this simulated roadway, store in the database of dynamic section, processor 201 is also constantly updated described newly-generated section data according to the new trace information of uploading in real time.
Optionally, the quantity of track and the acquisition time of track of processor 201 specifically for uploading in real time according to a plurality of mobile terminals, calculate on a certain section the on average consuming time of the track in region sometime, and average consuming timely as an instant motional impedance, be stored in a database using described, described a certain section is newly-generated section on section on original road or unknown road;
The path planning request of a certain particular requirement proposing when mobile terminal is: during the path planning request of shortest time, described processor is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculating a certainly has the corresponding path planning of path planning request of particular requirement specifically to comprise: the database data that has comprised these instant motional impedances for described processor, calculated population the shortest path planning consuming time.
Optionally, processor 201 is specifically for the acquisition time that is included in the track that numerous mobile terminals of travelling on original road and unknown road upload is stored in the dynamic data base of cloud platform, and the acquisition time of described track is associated with the acquisition time corresponding road section of described track; When mobile terminal is set a time zone; and file a request: when some are stored in track acquisition time in described dynamic data base while falling into described time zone; find out the corresponding track of these acquisition times; find out again the section at the track place of described correspondence; then with these sections, splice a path planning; qualified section is used in the request according to mobile terminal of 201 of processors, calculates path planning.
Optionally, the quantity of the track on certain section that processor 201 is uploaded numerous terminals, stores in the database of cloud platform, and is associated with corresponding road section; When mobile terminal is set an amount threshold, and when proposing track quantity on some sections and falling into this amount threshold, find out these sections, while then splicing the request of a path planning with these sections, qualified section is used in the request according to mobile terminal of 201 of processors, the planning of splicing outbound path.
Optionally, processor 201 specifically for by check in unknown road and the original road track quantity on region, a certain appointment section sometime, simulation generates and allows turning, no turn traffic restricted information, allows to turn around, no turns traffic restricted information or one-way road traffic restricted information.
Optionally, processor 201 is specifically for checking two crossing sections whether to own the track of certain travel direction of continuous same mobile terminal formation together, and calculate in the time zone of a setting absolute quantity of track described in this class, or the relative populations of comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information that can turn according to track travel direction at crossing node between these two sections, store in a special database, otherwise, when this result of calculation is less than a value of setting in advance, simulation generate between these two sections at crossing node according to the traffic restricted information of track travel direction no turn, store a special database into.
Optionally, processor 201 is specifically for the forward checking some sections whether to exist to take same mobile terminal that certain shape value point is turning point and form continuously and reverse track, and calculate in the time zone of a setting absolute quantity of track described in this class, or, the relative populations of comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information that can turn around according to described track turnover direction at this turning point between this section, store in a special database, otherwise, when this result of calculation is less than a value of setting in advance, simulation generate between this section at this turning point according to the described track turnover direction traffic restricted information that no turns, store in a special database.
Optionally, the track quantity of processor 201 specifically for checking the mobile terminal of certain direction of section of certain to form, and calculate in the time zone of a setting absolute quantity of track described in this class, or, the relative populations of comparing with track rightabout or that other are relevant, when this result of calculation is less than a value of setting in advance, simulation generates this section direction traffic restricted information that no through traffic described in this, stores in a special database.
Optionally, processor 201 is specifically for first adopting static conventional shortest path computing method to calculate the shortest path planning scheme of n bar overall distance, in n bar shortest path planning scheme, according to the instant motional impedance on section, place, select an overall the shortest paths planning consuming time again, described section comprises: the section on original road and unknown road.
Optionally, the conventional shortest path computing method of above-mentioned static state, refer to A* heuristic search algorithm; Described A* heuristic search algorithm is for calculating the shortest path planning scheme of n bar overall distance according to the dynamic section database data of described renewal and perfect cloud platform inside; Described A* heuristic search algorithm, is limited to a kind of special case of 0 A* heuristic search algorithm: dijkstra algorithm under comprising.
Optionally, above-mentionedly utilize described a plurality of trace information upgrade and improve at the dynamic section of cloud platform inside database, refer to after the new section data that simulation generates according to trace information, new section data are stored in a database of expressing in adjacency list mode together with original section data.
Optionally, processor 201 specifically for by the elevation in trace information and two dimension or three-dimensional motion directional information is associated with section, place and weighted mean after be stored in the database of dynamic section, when the difference but surface level position is close or identical highly up and down that comprises overpass for cloud platform, or approximate section of approaching of other highly identical but horizontal level is while carrying out path planning, first cloud platform checks the latitude and longitude coordinates of described approximate section node, when the corresponding differences of longitude coordinate value of node in two sections and the absolute value of the difference of latitude coordinate values are less than a setting threshold simultaneously, automatically read travel dispersed elevation and the travel direction of track thereon, calculate the joining relation with adjacent section, front and back simultaneously, the row labels of going forward side by side and prompting, then by described expression elevation, the mark of travel direction and joining relation, prompting sends to mobile terminal together with the path planning scheme calculating, the joining relation in the adjacent section of described calculating and front and back, refer to and calculate absolute quantity and the relative populations that the same direction of same mobile terminal is crossed over the continuous path in adjacent section, when described absolute quantity and relative populations fall into the amount threshold of setting in the time zone of a setting, confirming as these two sections has joining relation in the direction of this track operation.
Optionally, the described dynamic section database that utilizes described trace information or the existing real-time route programme of terminal to upgrade and improve cloud platform inside, refer to the existing real-time route programme of terminal that cloud platform is uploaded dynamically in real time according to a plurality of mobile terminals, and the instant motional impedance within the scope of a period of time in involved section, calculate a pre-quantitation of the mobile terminal on following a certain section of certain fixed time, then according to described pre-quantitation, found out the weighted mean value of the instant motional impedance in upper certain a period of time in this section corresponding with described pre-quantitation of storing in cloud platform, prediction motional impedance as this section, described prediction motional impedance and corresponding time are stored into together in the dynamic section database of cloud platform, when a mobile terminal proposes a certain specific path planning, cloud platform is according to described prediction motional impedance, the predict future fixed time, certain specifies the traffic congestion situation in section, and calculate a path planning scheme by the requirement of a certain specific path planning of mobile terminal proposition, send to mobile terminal.
It will be understood by those skilled in the art that all or part of step of technical scheme that the embodiment of the present invention provides is to complete by the relevant hardware of programmed instruction.Such as completing by computer run journey.This program can be stored in read/write memory medium, for example, and random access memory, disk, CD etc.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all being equal to of doing within the specific embodiment of the present invention, replace or improvement etc., within all should being included in protection scope of the present invention.

Claims (14)

1. a dynamic navigation path planning method, is characterized in that, described method comprises:
Cloud platform real-time radio receives a plurality of trace informations or the existing real-time route programme of a plurality of terminal that a plurality of mobile terminals are uploaded, then utilize described a plurality of trace information or a plurality of terminal to have real-time route programme, upgrade and improve the dynamic section database of cloud platform inside;
When a certain path planning request that has a particular requirement that cloud platform receives that mobile terminal proposes, cloud platform is according to upgrading and the dynamic section database data of perfect described cloud platform inside, calculate corresponding path planning, then the path planning of described correspondence is sent to mobile terminal with wireless mode;
Described trace information comprises: the quantity of track and the acquisition time of track, the longitude and latitude of track each point and acquisition time, elevation and acquisition time, two dimension or three-dimensional velocity and acquisition time, two dimension or three-dimensional motion direction and acquisition time, video or photo and acquisition time, the code of mobile terminal under track;
The existing real-time route programme of described terminal refer to that mobile terminal is inner existing and using, from described mobile terminal, this uploads location while starting to a path planning scheme of destination;
Described renewal and improve the dynamic section database of cloud platform inside, refer to and comprise: according to the trace information that comprises the quantity of track and the acquisition time of track, generate and upgrade the section data on unknown road, generate and upgrade the instant motional impedance in all sections, generate and upgrade the simulation traffic restricted information in all sections; In addition, according to the existing real-time route programme of described a plurality of terminals and track historical data, generate and upgrade the prediction motional impedance in all sections;
Described all sections refer to and comprise newly-generated section and original section; The acquisition time of described track, the corresponding associated time of of being comprised of the acquisition time that forms the longitude and latitude of track each point and described each point that refers to gathers; The acquisition time of the longitude and latitude of described track each point, refers to mobile terminal residing moment when getting the latitude and longitude coordinates of described each point.
2. method according to claim 1, is characterized in that, described generation and upgrade the section data on unknown road specifically comprises:
When mobile terminal travels and uploads trace information on unknown road, cloud platform is by the positional information in described trace information, remove abnormity point and noise and arrange and be merged into one or more simulated roadway according to certain method, keep in the database of dynamic section, simultaneously the track quantity in cumulative described simulated roadway; In the time zone in a certain setting, when being incorporated in cumulative described track quantity on certain described simulated roadway and falling into a certain setting threshold, cloud platform is transformed into one or several new temporary or permanent newly-generated section data by described certain described simulated roadway, store in the database of dynamic section, then cloud platform is constantly updated described newly-generated section and related data according to the new trace information of uploading in real time;
Described unknown road refers to the road that there is no corresponding data in the database of original described dynamic section.
3. method according to claim 1, is characterized in that, described in calculate corresponding path planning and specifically comprise:
The quantity of the track that cloud platform is uploaded in real time according to a plurality of mobile terminals and the acquisition time of track, calculate on a certain section the on average consuming time of the track in region sometime, and average consuming timely as an instant motional impedance, with described time zone, be stored in together in a database using described, described a certain section refers to newly-generated section on section on original road or unknown road;
When what mobile terminal proposed, a certainly there is the path planning request of particular requirement to be: during the path planning request of shortest time, described cloud platform is according to the dynamic section database data of described renewal and perfect cloud platform inside, calculating corresponding path planning specifically comprises: the database data that has comprised these instant motional impedances for cloud platform, calculates overall the shortest path planning consuming time.
4. method according to claim 1, is characterized in that, described in calculate corresponding path planning and specifically comprise:
Cloud platform stores the acquisition time that is included in the track that a plurality of mobile terminals of travelling on original road and unknown road upload in the dynamic data base of cloud platform into, and the acquisition time of described track is associated with the section at corresponding track place; When cloud platform or mobile terminal are set a time zone, and file a request: when some are stored in track acquisition time in the database of described dynamic section while falling into described time zone, find out the corresponding track of this acquisition time, find out again the section at the track place of described correspondence, then with these sections, splice a path planning; Cloud platform is used qualified section according to the request of cloud platform or mobile terminal, calculates corresponding path planning.
5. method according to claim 1, is characterized in that, described in calculate corresponding path planning and specifically comprise:
The quantity of the track on certain section that cloud platform is uploaded a plurality of mobile terminals is calculated, and stores in the database of cloud platform, and is associated with corresponding road section; When cloud platform or track amount threshold of mobile terminal setting or track quantity ratio threshold value, and file a request: when the quantity of the track on some sections falls into described in this track amount threshold, or the ratio of the quantity of the track on some sections and the quantity of relevant track is while falling into described in this track quantity ratio threshold value, find out more described sections, then with more described sections, splice a path planning; Cloud platform according to the request of cloud platform or mobile terminal with qualified more described sections, splice respective path planning.
6. method according to claim 1, is characterized in that, described renewal and the dynamic section database that improves cloud platform inside also comprise:
By check continuous path quantity or relative populations in region, certain some specified circuit section sometime on unknown road or original road, simulation generate to allow is turned, no turn traffic restricted information, allows to turn around, no turns traffic restricted information or accurate one-way traffic traffic restricted information only.
7. method according to claim 6, is characterized in that, described simulation generates and allows turning or no turn traffic restricted information to comprise:
Whether two crossing sections of cloud platform check own the track of certain continuous turn direction of same mobile terminal formation together, and the relative populations of calculating in the time zone of a setting quantity of track described in this class or comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information of turning according to described certain turn direction permission at crossing node between these two sections, stores in a special database; Otherwise, when this result of calculation is less than a value of setting in advance, simulation generate between these two sections at crossing node according to the traffic restricted information of described certain turn direction no turn, store in a special database.
8. method according to claim 6, is characterized in that, described simulation generation allows to turn around or no turns, and traffic restricted information comprises:
Cloud platform checks some sections whether to exist to take forward that same mobile terminal that certain shape value point is turning point forms continuously and reverse track, and calculate in the time zone of a setting quantity of track described in this class, or, the relative populations of comparing with relevant track, when this result of calculation is greater than a value of setting in advance, simulation generates the traffic restricted information that the permission between this section is turned around according to described track turnover direction at this turning point, stores in a special database; Otherwise when this result of calculation is less than a value of setting in advance, simulation generates the traffic restricted information that forbidding between this section turn around according to described track turnover direction at this turning point, stores in a special database.
9. method according to claim 6, is characterized in that, described simulation generates only accurate one-way traffic traffic restricted information and comprises:
The track quantity that cloud platform checks the mobile terminal of certain assigned direction in certain section to form, and calculate in the time zone of a setting quantity of track described in this class, or, the relative populations of comparing with track rightabout or that other are relevant, when this result of calculation is less than a value of setting in advance, simulation generates this section certain assigned direction traffic restricted information that no through traffic described in this, stores in a special database.
10. method according to claim 1, is characterized in that, described cloud platform calculates corresponding path planning according to described renewal and the data of improving the dynamic section database of described cloud platform inside and comprises:
Cloud platform first adopts static conventional shortest path computing method to calculate the shortest path planning scheme of n bar overall distance, in the shortest path planning scheme of described n bar overall distance, according to the instant motional impedance on included section, calculate an overall the shortest paths planning consuming time again, described section comprises: the section on original road and unknown road.
11. methods according to claim 10, is characterized in that, the conventional shortest path computing method of described static state, refer to A *heuristic search algorithm; And described A *heuristic search algorithm is for calculating the shortest path planning scheme of n bar overall distance according to the dynamic section database data of described renewal and perfect cloud platform inside; Described A *heuristic search algorithm, is limited to 0 A under comprising *a kind of special case of heuristic search algorithm: dijkstra algorithm.
12. methods according to claim 1, it is characterized in that, described renewal and improve the dynamic section database of cloud platform inside, refer to the section data on the described unknown road by generation and after upgrading, with original section data, be stored in together in a database of expressing in adjacency list mode.
13. methods according to claim 1, it is characterized in that, described cloud platform, according to the dynamic section database data of described renewal and perfect cloud platform inside, calculates and the described a certain corresponding path planning of path planning request that has particular requirement, specifically comprises:
Weighted mean value or the video photo of the elevation weighted mean value of each position point in trace information or two dimension, three-dimensional motion directional data are associated with storing in database with section, place, in order to distinguish approximate section; When retrieving, cloud platform comprises overpass difference but surface level position is close or identical or that other highly identical but horizontal level approaches described in some during approximate section highly up and down, described in further quantitative comparison, be similar to again the latitude and longitude coordinates of section node, when the corresponding differences of longitude coordinate value of node in two sections and the absolute value of the difference of latitude coordinate values are less than the value of a setting simultaneously, extract the trace information that comprises dispersed elevation, average travel direction, video, photo travelling at described two mobile terminals above section; Or calculate the joining relation in described two sections and adjacent section, front and back separately simultaneously, the row labels of going forward side by side and prompting, be stored in a special dynamic section database; When mobile terminal proposes a certain path planning request that has a particular requirement, cloud platform comprises described dispersed elevation, average travel direction, video, the trace information of photo or the data of joining relation with being stored in described special dynamic section database, calculates corresponding path planning; Then by the trace information of described dispersed elevation, average travel direction, video, photo or described joining relation together with mark and prompting, with the path planning scheme calculating together, send to mobile terminal; Described link for calculating relation, refer to the resulting quantity that each mobile terminal on cumulative certain section is crossed over the continuous path forming when node drives to adjacent section in craspedodrome or turning process, the relative value of comparing with other relevant track quantity when value or the described quantity of quantity described in this, while being greater than the value of a setting in the time zone of a setting, confirming as these two sections and take the node crossed over as being connected point, having joining relation in the direction of this track operation.
14. methods according to claim 1, it is characterized in that, describedly calculate corresponding path planning and specifically comprise: the existing real-time route programme of terminal that cloud platform is uploaded dynamically in real time according to a plurality of mobile terminals, and the instant motional impedance in involved section, calculate a pre-quantitation of the mobile terminal on a certain appointment of following a certain fixed time section, then according to described pre-quantitation, find out some the instant motional impedances on this section corresponding with described pre-quantitation of storing in cloud platform, the resulting numerical value of more described instant motional impedance weighted means is to the prediction motional impedance in a certain appointment of a certain fixed time in described future section, described prediction motional impedance will be stored into together with a certain fixed time in described future in the dynamic section database of cloud platform, when a mobile terminal proposes a certain specific path planning, cloud platform is according to described prediction motional impedance, predict the traffic congestion situation in a certain appointment of a certain fixed time in described future section, and using described prediction motional impedance as one of parameter, calculate a respective path programme, send to mobile terminal.
CN201310466623.3A 2013-10-09 2013-10-09 Dynamic trajectory navigation method and cloud platform Active CN103557870B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201310466623.3A CN103557870B (en) 2013-10-09 2013-10-09 Dynamic trajectory navigation method and cloud platform
PCT/CN2014/087686 WO2015051718A1 (en) 2013-10-09 2014-09-28 Dynamic track navigation method and cloud platform

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310466623.3A CN103557870B (en) 2013-10-09 2013-10-09 Dynamic trajectory navigation method and cloud platform

Publications (2)

Publication Number Publication Date
CN103557870A CN103557870A (en) 2014-02-05
CN103557870B true CN103557870B (en) 2014-11-12

Family

ID=50012180

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310466623.3A Active CN103557870B (en) 2013-10-09 2013-10-09 Dynamic trajectory navigation method and cloud platform

Country Status (2)

Country Link
CN (1) CN103557870B (en)
WO (1) WO2015051718A1 (en)

Families Citing this family (62)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103557870B (en) * 2013-10-09 2014-11-12 董路 Dynamic trajectory navigation method and cloud platform
IN2013MU03275A (en) * 2013-10-18 2015-07-03 Singh Puri Vikramjeet
US9779606B2 (en) 2013-10-25 2017-10-03 Beijing Qihoo Technology Company Limited Methods, devices, and systems for prompting whether portable locator has arrived on time
CN103561070B (en) * 2013-10-25 2016-08-17 北京奇宝科技有限公司 Point out the carry-on location method and device that equipment arrives at the most on time, system
CN104240500A (en) * 2014-08-25 2014-12-24 奇瑞汽车股份有限公司 Road condition information predicting method and system
CN104217109A (en) * 2014-09-01 2014-12-17 中国人民解放军国防科学技术大学 Method for realizing hybrid and active scheduling on quick satellites
CN104715628A (en) * 2014-12-23 2015-06-17 上海语镜汽车信息技术有限公司 Vehicle-mounted real-time road condition method and device based on positional relationship calculation
CN104501825B (en) * 2015-01-15 2017-07-25 刘畅 A kind of dynamic navigation method and equipment based on multidate information
CN104567908B (en) * 2015-01-22 2017-06-23 北京微车一族信息技术发展有限公司 It is a kind of can offline field driving digital map navigation method
CN105046983B (en) * 2015-08-14 2019-01-25 奇瑞汽车股份有限公司 A kind of traffic flow forecasting system and method based on bus or train route collaboration
CN105448088A (en) * 2015-11-20 2016-03-30 浪潮集团有限公司 Traffic condition monitoring method and system based big data
CN105547311A (en) * 2015-12-08 2016-05-04 深圳天珑无线科技有限公司 Route planning method, mobile terminal, and system
CN105446338B (en) * 2015-12-21 2017-04-05 福州华鹰重工机械有限公司 Cloud aids in automatic Pilot method and system
CN106023629B (en) * 2016-06-06 2018-12-25 西安电子科技大学昆山创新研究院 A kind of path recommended method and device
DE102016210745A1 (en) * 2016-06-16 2017-12-21 Robert Bosch Gmbh Updating navigation data
CN106840199B (en) * 2016-12-28 2019-07-09 北京市天元网络技术股份有限公司 A kind of calibration method and system of navigation of display data
CN106679685B (en) * 2016-12-29 2020-07-17 鄂尔多斯市普渡科技有限公司 Driving path planning method for vehicle navigation
CN107063281A (en) * 2017-04-12 2017-08-18 杨政超 Automobile navigation method, device and terminal
CN107221195B (en) * 2017-05-26 2020-03-17 重庆长安汽车股份有限公司 Automobile lane prediction method and lane level map
CN107192399B (en) * 2017-06-30 2020-02-18 Oppo广东移动通信有限公司 Navigation method, navigation device, storage medium and terminal
CN107146416B (en) * 2017-07-18 2020-01-21 深圳市锦粤达科技有限公司 Intelligent traffic management system
CN107481520B (en) * 2017-07-21 2021-03-23 清华大学 Road transport vehicle overrun information identification method based on floating car technology
CN108151755A (en) * 2017-12-21 2018-06-12 江西爱驰亿维实业有限公司 Air navigation aid, device and computing device based on more members
CN109959380A (en) * 2017-12-22 2019-07-02 中南大学 A kind of determination method of the passage door based on vehicle mounted guidance track characteristic
CN108189927B (en) * 2017-12-27 2023-11-28 广东嘉腾机器人自动化有限公司 Method for tracking AGV device in branch road section and merging road section and AGV transport vehicle
CN108615389A (en) * 2018-06-15 2018-10-02 邵文远 A kind of urban traffic blocking FORECAST AND PREVENTION system
CN110736462A (en) * 2018-07-20 2020-01-31 上海擎感智能科技有限公司 Method and device for comparing multiple planned routes
CN110889962B (en) * 2018-09-07 2022-09-30 上海擎感智能科技有限公司 Planned route and track route comparison method and device
CN110645997B (en) * 2018-09-30 2021-08-20 北京奇虎科技有限公司 Method and device for digging new roads based on track route
CN111081010B (en) * 2018-10-18 2022-08-02 阿里巴巴集团控股有限公司 Method and device for predicting traffic flow or travel time
CN109543575B (en) * 2018-11-09 2023-09-01 深圳市云兴科技有限公司 Method for feeding back excitation big data based on behavior track and dynamic multi-dimensional information and regional multi-dimensional detection feedback combined equipment
CN111210616A (en) * 2018-11-21 2020-05-29 上海博泰悦臻网络技术服务有限公司 Vehicle flow prediction method, system, terminal and medium based on multi-source data
CN109639805A (en) * 2018-12-19 2019-04-16 上海上实龙创智慧能源科技股份有限公司 A kind of cooperative control method of edge side and cloud
CN109708654A (en) * 2018-12-29 2019-05-03 百度在线网络技术（北京）有限公司 A kind of paths planning method and path planning system
CN111405480B (en) * 2019-01-02 2022-04-29 ***通信有限公司研究院 Road condition information pushing method, network equipment, vehicle-mounted terminal and system
CN109949351B (en) * 2019-03-19 2022-10-04 郑州信大先进技术研究院 Target vehicle running track extraction device and method based on video structured monitoring
CN111813820A (en) * 2019-04-12 2020-10-23 北京三快在线科技有限公司 Method, device, storage medium and electronic equipment for determining blocked road section
CN110260872B (en) * 2019-05-06 2023-08-01 合肥工业大学 Dynamic overtaking track planning system based on GPS under vehicle-road cooperative environment
CN110111421B (en) * 2019-05-10 2023-01-31 武汉海达数云技术有限公司 Method and device for mobile mapping point cloud
CN110348092B (en) * 2019-06-28 2023-12-08 浙江吉利控股集团有限公司 Track data simulation method and device
CN110645989B (en) * 2019-10-16 2021-03-02 众虎物联网(广州)有限公司 Path planning method and device based on escalator running direction and storage medium
CN111062970A (en) * 2019-12-10 2020-04-24 广州电力工程监理有限公司 Track generation method and system based on thermodynamic diagram
CN111382957A (en) * 2020-03-30 2020-07-07 中国铁塔股份有限公司 Infrastructure planning method and device and electronic equipment
CN113706857B (en) * 2020-05-22 2022-11-08 百度在线网络技术（北京）有限公司 Method, device and equipment for determining road trafficability and storage medium
CN113721599B (en) * 2020-05-25 2023-10-20 华为技术有限公司 Positioning method and positioning device
CN111717222B (en) * 2020-06-30 2022-04-12 深圳市元征科技股份有限公司 Vehicle control method and related equipment
CN112069277B (en) * 2020-09-03 2024-03-22 深圳市自然资源和不动产评估发展研究中心(深圳市地质环境监测中心) Stratum attribute abnormal point presentation method, system and equipment based on digital map
CN112289057A (en) * 2020-09-30 2021-01-29 深圳市金溢科技股份有限公司 Vehicle-road cooperative automatic driving assistance method and system, processing equipment and vehicle-mounted equipment
CN114516044A (en) * 2020-11-20 2022-05-20 炬星科技（深圳）有限公司 Robot path planning method, device and storage medium
CN112734167B (en) * 2020-12-20 2023-04-07 中国电子科技集团公司第二十研究所 Heterogeneous warning aircraft continuous patrol strategy planning method
CN113074745B (en) * 2021-02-24 2024-03-19 南京泛析交通科技有限公司 Urban road cleaning vehicle path planning method and device
CN113129630B (en) * 2021-03-30 2022-08-12 中国联合网络通信集团有限公司 Autonomous parking method, AVP platform and vehicle terminal
CN113393571B (en) * 2021-06-15 2023-06-27 北京市遥感信息研究所 Cloud-free satellite image generation method and device
CN114184202A (en) * 2021-11-01 2022-03-15 浙江大华技术股份有限公司 Path planning method and device
CN114295117B (en) * 2021-11-29 2023-09-12 惠州华阳通用智慧车载***开发有限公司 Road updating method for vehicle navigation map
CN113866734B (en) * 2021-12-03 2022-03-04 中国电子科技集团公司信息科学研究院 Method and device for correcting track error of distributed radar system
CN114383617A (en) * 2021-12-29 2022-04-22 深圳市跨越新科技有限公司 Navigation route calculation method, device, equipment and storage medium based on map neural network
CN114442627B (en) * 2022-01-24 2023-10-13 电子科技大学 Dynamic desktop path finding system and method for intelligent home mobile equipment
CN114674339B (en) * 2022-05-26 2022-08-12 文诚恒远(天津)供应链管理服务有限公司 Truck navigation method and device
CN115167406B (en) * 2022-06-28 2024-05-17 智己汽车科技有限公司 Method and equipment for generating dynamic automatic driving global path
CN114923478B (en) * 2022-07-20 2022-10-25 杭州锦辉科技有限公司 Navigation path management method and system and electronic equipment
CN117405124B (en) * 2023-12-13 2024-02-27 融科联创(天津)信息技术有限公司 Path planning method and system based on big data

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102385804A (en) * 2010-08-30 2012-03-21 谈宇清 Intelligent traffic system and navigation method thereof
US8483959B2 (en) * 2011-01-06 2013-07-09 Telenav, Inc. Navigation system with location adaptation and method of operation thereof
CN102735251B (en) * 2011-04-01 2014-12-17 深圳市赛格导航科技股份有限公司 Cloud computing based GPS navigation method and system
US8874366B2 (en) * 2011-05-23 2014-10-28 Microsoft Corporation First waypoint distance
KR101786737B1 (en) * 2011-06-22 2017-11-15 에스케이플래닛 주식회사 System and method for partial updating of map data based on use's moving path, terminal device and recording medium thereof
CN102436003A (en) * 2011-11-10 2012-05-02 浪潮电子信息产业股份有限公司 Cloud computing-based GPS (Global Positioning System) positioning method
CN102853842B (en) * 2012-05-15 2013-10-16 董路 Navigation path planning method, apparatus, and system
CN103557870B (en) * 2013-10-09 2014-11-12 董路 Dynamic trajectory navigation method and cloud platform

Also Published As

Publication number Publication date
CN103557870A (en) 2014-02-05
WO2015051718A1 (en) 2015-04-16

Similar Documents

Publication Publication Date Title
CN103557870B (en) Dynamic trajectory navigation method and cloud platform
RU2734744C1 (en) Operational control of autonomous vehicle, including operation of model instance of partially observed markov process of decision making
RU2733015C1 (en) Real-time vehicle control
CN101964148B (en) Road traffic information recording server and GPS (Global Positioning System) user terminal
RU2734732C1 (en) Traffic network blocking tracking during operational control of autonomous vehicle
CN110709908B (en) Computer system and method for state prediction of traffic system
US11625051B2 (en) Proactive generation of tuning data for autonomous vehicle dispatch
CN105074793A (en) Lane-level vehicle navigation for vehicle routing and traffic management
CN107331200A (en) A kind of CBD underground garages intelligent parking guiding system, method and device
EP3836116A1 (en) System and method to generate traffic congestion estimation data for calculation of traffic condition in a region
WO2021168845A1 (en) Navigation method and apparatus
CN104884899A (en) Method of determining trajectories through one or more junctions of a transportation network
CN104937650A (en) System and method for locating available parking spaces
JP2014527617A (en) Route provision through information collection and extraction
JPH10319839A (en) Pedestrian information service system
CN111351492A (en) Method and system for autonomous vehicle navigation
CN103759735A (en) Firefighting vehicle-oriented navigation system
CN108332761B (en) Method and equipment for using and creating road network map information
Bachechi et al. Implementing an urban dynamic traffic model
US10429200B1 (en) Determining adjusted trip duration using route features
Boubakri et al. High definition map update for autonomous and connected vehicles: A survey
Lee et al. Development of reinforcement learning-based traffic predictive route guidance algorithm under uncertain traffic environment
KR102377652B1 (en) Pedestrian traffic information providing system and method using controlled traffic signal informationttg
Wilkie et al. Participatory route planning
Lv et al. Optimization of dynamic parking guidance information for special events

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant